Design of a Control System for Serial Mechanisms

2016 ◽  
Author(s):  
Dan Zhang ◽  
Bin Wei
Keyword(s):  
Control System ◽  
Dynamic Equation ◽  
Degrees Of Freedom ◽  
Nonlinear Term ◽  
Hybrid Control ◽  
Adaptive Controller ◽  
Hybrid Controller ◽  
Speed Performance ◽  
Convergence Performance ◽  
Model Reference Adaptive

A hybrid control system for multi degrees of freedom robotic manipulator is designed by integrating a proportional-integral-derivative controller (PID) and a model reference adaptive controller (MRAC) in order to further improve the accuracy and joint convergence speed performance. For the 1-DOF link, because the inertia matrices and nonlinear term of the dynamic equation are constant, we can directly combine the PID and MRAC controller to design the PID+MRAC controller. However, for the more than 1-DOF link case, it is no longer applicable because the inertia matrices and nonlinear term of the dynamic equation are not constant. By using an improved adaptive algorithm and structure, and by combining the PID and improved MRAC controllers, a controller is designed for the more than 1-DOF link case. The convergence performance of the PID controller, MRAC and the PID+MRAC hybrid controller for 1-DOF, 2-DOF and subsequently 3-DOF manipulators are compared.

Synthesis Design and Analysis of a Hybrid Controller for Robotic Arms

2016 ◽  
Author(s):  
Dan Zhang ◽  
Bin Wei
Keyword(s):  
Pid Controller ◽  
Adaptive Controller ◽  
Convergence Speed ◽  
Model Reference ◽  
Robotic Arms ◽  
Hybrid Controller ◽  
Comparison Results ◽  
Convergence Performance ◽  
Model Reference Adaptive ◽  
Better Than

In this paper, a hybrid controller for robotic arms is proposed and designed by combining a proportional-integral-derivative controller (PID) and a model reference adaptive controller (MRAC) in order to further improve the accuracy and joint convergence speed performance. The convergence performance of the PID controller, the model reference adaptive controller and the PID+MRAC hybrid controller for 1-DOF and 2-DOF manipulators are compared. The comparison results show that the convergence speed and its performance for the MRAC and the PID+MRAC controllers are better than that of the PID controller, and the convergence performance for the hybrid control is better than that of the MRAC control.

Design, analysis and modelling of a hybrid controller for serial robotic manipulators

Robotica ◽  
2016 ◽  
Vol 35 (9) ◽  
pp. 1888-1905 ◽  
Author(s):  
Dan Zhang ◽  
Bin Wei
Keyword(s):  
Pid Controller ◽  
Robotic Manipulators ◽  
Convergence Speed ◽  
Model Reference ◽  
Control Approach ◽  
Hybrid Controller ◽  
Comparison Results ◽  
Convergence Performance ◽  
Model Reference Adaptive ◽  
Better Than

SUMMARYWhen the end-effector of a robotic arm grasps different payload masses, the output of joint motion will vary. By using a model reference adaptive control approach, the payload variation effect can be solved. This paper describes the design for a hybrid controller for serial robotic manipulators by combining a PID controller and a model reference adaptive controller (MRAC) in order to further improve the accuracy and joint convergence speed performance. The convergence performance of the PID controller, the MRAC and the PID+MRAC hybrid controller for 1-DOF, 2-DOF and subsequently 3-DOF manipulators is compared. The comparison results show that the convergence speed and its performance for the MRAC and the PID+ MRAC controllers is better than that of the PID controller, and the convergence performance for the hybrid control is better than that of the MRAC control.

scholarly journals Experimental simplified rule of self tuning fuzzy logic-model reference adaptive speed controller for induction motor drive

2020 ◽  
Vol 20 (3) ◽  
pp. 1653
Author(s):  
M.Z. Ismail ◽  
M.H.N. Talib ◽  
Z. Ibrahim ◽  
J. Mat Lazi ◽  
Z. Rasin
Keyword(s):  
Fuzzy Logic ◽  
Induction Motor ◽  
Fuzzy Logic Controller ◽  
Adaptive Controller ◽  
Tuning Parameter ◽  
Model Reference ◽  
Wide Range ◽  
Speed Performance ◽  
Self Tuning ◽  
Model Reference Adaptive

<span>Fuzzy logic controller (FLC) has shown excellent performance in dealing with the non-linearity and complex dynamic model of the induction motor. However, a conventional constant parameter FLC (CPFL) will not be able to provide–good coverage performance for a wide speed range operation with a single tuning parameter. Therefore, this paper proposed a self tuning mechanism FLC approach by model reference adaptive controller (ST-MRAC) to continuously allow to adjust the parameters. Due to real time hardware application, the dominant rules selection method for simplified rules has been implemented as part of the reducing computational burden. Experiment results validate a good performance of the ST-MRAC compared to the CPFL for the   speed performance in terms of the wide range of operations and disturbance showed remarkable performance.</span>

scholarly journals Design and Simulation of Eight-Rotor Unmanned Aerial Vehicle Based on Hybrid Control System

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Xueqiang Shen ◽  
Jiwei Fan ◽  
Haiqing Wang
Keyword(s):  
Control System ◽  
Unmanned Aerial Vehicle ◽  
Flight Control ◽  
Hybrid Control ◽  
Dynamic Performance ◽  
System Response ◽  
Hybrid Controller ◽  
Aerial Vehicle ◽  
Switching Method ◽  
Hybrid Control System

In order to control the position and attitude of unmanned aerial vehicle (UAV) better in different environments, this study proposed a hybrid control system with backstepping and PID method for eight-rotor UAV in different flight conditions and designed a switching method based on altitude and attitude angle of UAV. The switched process of hybrid controller while UAV taking off, landing, and disturbance under the gust is verified in MATLAB/Simulink. A set of appropriate controllers always matches to the flight of UAV in different circumstances, which can speed up the system response and reduce the steady-state error to improve stability. The simulation results show that the hybrid control system can suppress the drift efficiently under gusts, enhance the dynamic performance and stability of the system, and meet the position and attitude of flight control requirements.

scholarly journals HYBRID CONTROL SYSTEM IN BIONIC LEG USING MYOWARE SENSOR

2021 ◽  
Vol 56 (4) ◽  
pp. 104-116
Author(s):  
W. Widhiada ◽  
M.A. Parameswara ◽  
I.G.N.N. Santhiarsa ◽  
I.N. Budiarsa ◽  
I.M.G. Karohika ◽  
...  
Keyword(s):  
Control System ◽  
Steady State ◽  
Hybrid Control ◽  
Persons With Disabilities ◽  
Hybrid Controller ◽  
Innovation Product ◽  
Programming Software ◽  
Hybrid Control System ◽  
System Time ◽  
State Error

A bionic robot leg (BRL) is a contrivance used to supersede a loss component of the lower limb due to amputation or congenital disability. Hybrid control of BRL is opted to obtain the maximum performance of BRL equipped with precise forms of kineticism and expeditious response by truncating the error and maximum overshoot and reducing time settle. This research aims to create a BRL innovation product for persons with disabilities at the Bali Puspadi Foundation. The novelty of this BRL is the implementation of the algorithm as outlined in the hybrid control system in the Arduino support package. The BRL utilizes a MyoWare sensor and an Arduino Mega 2560 microcontroller equipped with Matlab/Simulink R2020a programming software. The sensor is utilized to read the angular movement of the DC motor between 0 - 60° degrees and vice versa, following the concept of the gate cycle. The results obtained from the hybrid control simulation are 0.0713% on maximum overshoot, 0.0415% on steady-state error, and 1.292s on system time settle. Furthermore, the results obtained from the hybrid controller experiment are 0.627% on maximum overshoot, 0.257% on steady-state error, and 0.8s on system time settle.

scholarly journals Adaptive augmentation of the attitude control system for a multirotor unmanned aerial vehicle

2018 ◽  
Vol 234 (10) ◽  
pp. 1587-1596
Author(s):  
G Bressan ◽  
A Russo ◽  
D Invernizzi ◽  
M Giurato ◽  
S Panza ◽  
...  
Keyword(s):  
Control System ◽  
Unmanned Aerial Vehicle ◽  
Attitude Control ◽  
Adaptive Controller ◽  
Attitude Control System ◽  
Loop Dynamics ◽  
The Standard Model ◽  
Aerial Vehicle ◽  
Adaptation Law ◽  
Model Reference Adaptive

In this paper, the adaptive augmentation of the attitude control system for a multirotor unmanned aerial vehicle is considered. The proposed approach allows to combine a baseline controller with an adaptive one and to disable or enable the adaptive controller when needed, in order to take the advantages of both the controllers. To improve transient performance with respect to the standard model reference adaptive controller, an observed-based approach is exploited. The adaptation law is based on the error between the output of an observer of the nominal closed-loop dynamics and the actual output of the system with uncertainties. Experimental results obtained by testing the proposed approach on a quadrotor unmanned aerial vehicle are presented to compare the performance, in terms of disturbance rejection, with respect to the baseline controller and to a [Formula: see text] adaptive augmentation scheme.

Hybrid intelligent adaptive controller for tiltrotor UAV

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jafar Tavoosi
Keyword(s):  
Neural Network ◽  
Position Control ◽  
Control Method ◽  
Hybrid Control ◽  
Adaptive Controller ◽  
Content Type ◽  
Flight Mode ◽  
Horizontal Flight ◽  
Aerial Vehicle ◽  
Model Reference Adaptive

PurposeIn this paper, an innovative hybrid intelligent position control method for vertical take-off and landing (VTOL) tiltrotor unmanned aerial vehicle (UAV) is proposed. So the more accurate the reference position signals tracking, the proposed control system will be better.Design/methodology/approachIn the proposed method, for the vertical flight mode, first the model reference adaptive controller (MRAC) operates and for the horizontal flight, the model predictive control (MPC) will operate. Since the linear model is used for both of these controllers and naturally has an error compared to the real nonlinear model, a neural network is used to compensate for them. So the main novelties of this paper are a new hybrid control design (MRAC & MPC) and a neural network-based compensator for tiltrotor UAV.FindingsThe proper performance of the proposed control method in the simulation results is clear. Also the results showed that the role of compensator is very important and necessary, especially in extreme speed wind conditions and uncertain parameters.Originality/valueNovel hybrid control method. 10;-New method to use neural network as compensator in an UAV.

Modeling and Controlling the Dynamic Behavior of an Aerial Manipulator

2021 ◽  
pp. 2150044
Author(s):  
Zain Anwar Ali ◽  
Li Xinde
Keyword(s):  
Dynamic Behavior ◽  
Control Algorithm ◽  
Degrees Of Freedom ◽  
Control Mechanism ◽  
Hybrid Control ◽  
External Noise ◽  
Pole Placement ◽  
Aerial Manipulator ◽  
Aerial Vehicle ◽  
Model Reference Adaptive

Unmanned Aerial Vehicles (UAVs) installed with a gripper is an effective and robust way to grab the wanted object from inaccessible locations. In this study, we develop a novel control mechanism to regulate the nonlinear dynamics of the aerial manipulator. In this research, hex-rotor UAV is chosen in order to fulfill the mission requirement in terms of size and weight of the object. It is equipped with a manipulator and the gimbal-based camera that will help to see the desired object and then transport it. The aerial vehicle has six-degrees-of-freedom (6-DOF) and the installed manipulator has 4-DOF which in total makes the 10-DOF aerial manipulator vehicle. At the time of clutching the desired object to eliminate or reduce the external noise, and stabilize the dynamic behavior of the aerial manipulator, we need a robust and efficient controller. To solve the aforementioned problems, this study develops a hybrid control mechanism that tracks and controls the altitude and attitude of UAV after clutching the desired object. The main contribution of this study is to design a control mechanism that includes Model Reference Adaptive Control with an Integrator (MRACI) in conjunction with regulation, pole-placement and tracking (RST) control algorithm. On one hand, the simulation results using MATLAB demonstrate the efficiency of the proposed control mechanism. On the other hand, to cross verify the validity of the proposed control algorithm, we perform the experiment by clutching the desired object at hovering and normal flight operation.

Adaptive Control for Steering Engine Fault of Ducted Fan UAV

2014 ◽  
Vol 602-605 ◽  
pp. 834-843
Author(s):  
An Huang ◽  
Zhong Xi Hou
Keyword(s):  
Control System ◽  
Attitude Control ◽  
Adaptive Controller ◽  
Attitude Control System ◽  
Model Reference ◽  
Ducted Fan ◽  
Model Reference Adaptive ◽  
The Impact ◽  
The Relationship ◽  
Good Attitude

For the steering engine fault of ducted fan UAV that may arise during the hovering, designing adaptive controller for attitude control. First, concentrating on modeling of the hovering state of ducted fan UAV, and getting the relationship between steering engine and attitude control. Then analyzing the impact of steering engine fault on the attitude control system basing on the control model. Finally, designing model reference adaptive controller basing on the fault model, so that the ducted fan UAV can maintain good attitude control if steering engine fault occurs during the hovering. Simulation results show that when steering engine fault occurs, the model reference adaptive controller can effectively inhibit the adverse effects brought by steering engine fault, so the attitude control system has strong adaptability and robustness.

Gait Emulator for Evaluation of a Powered Ankle-Foot Prosthesis

2017 ◽  
Author(s):  
Evandro Ficanha ◽  
Houman Dallali ◽  
Mo Rastgaar
Keyword(s):  
Control System ◽  
Degrees Of Freedom ◽  
Closed Loop ◽  
Hybrid Control ◽  
Design Parameters ◽  
Parameter Uncertainties ◽  
Walking Tests ◽  
Walking Speeds ◽  
Hybrid Control System ◽  
Smooth System

In this paper we present an enhanced gait emulator and a novel hybrid control system to test powered ankle-foot prostheses with two degrees of freedom in the sagittal and frontal planes. The gait emulator is a nonlinear and non-smooth system that has to follow a precisely timed set of phases to achieve a human-like periodic gait. Despite the complexity and parameter uncertainties of this five degrees of freedom system, our proposed hybrid control system simplifies the walking control by use of state triggered kinematic events. The control system works in closed loop with kinematic event detection to ensure robust and repeatable walking tests as design parameters are varied. The developed gait emulator can be used to test the prosthesis under various loading conditions and walking speeds.

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